Following are public and technical abstracts for the Mitochondrial DNA Mutations project funded by the Department of Defense Kidney Cancer Research Program (KCRP) for 2017.
Principal Investigator: Eduard Reznik
Institution: Sloan Kettering Institute for Cancer Research
Funding Mechanism: Concept Award
Award Amount: $128,775
Public Abstract
Mutations in many genes interact to make kidney tumors malignant and aggressive. In this project, we examine how a set of common but understudied mutations to genes in the mitochondrial genome (mtDNA) affect kidney tumor cells. These genes are highly critical to the cell’s energy-making capabilities, but they are hard to study. Because many copies of mtDNA exist within each cell, it is possible only a subset of mtDNA, inside of a subset of cells, are mutated. To study these mutations, we use a technology that sequences mitochondrial RNA (a byproduct of mtDNA) from individual cells, allowing us to trace which cells have which mutation. This gives us unprecedented resolution and enables us to ask how cells with mtDNA mutations are different from those without them. The results from this work will inform us about the vulnerabilities present specifically in mtDNA-mutant kidney tumor cells and, in turn, will advance the research toward future therapeutic opportunities for American citizens with kidney cancer.
Technical Abstract
Despite their high incidence across diverse histologies of renal cell carcinoma (RCC), the effect of somatic mtDNA mutations on kidney tumor physiology is largely uncharacterized. Tracing the consequences of these mutations on cellular phenotypes is further confounded by the potential for mtDNA mutations to be subclonal, both within the bulk tumor and within a single cell. In this project, we hypothesize that mtDNA-mutant cells exhibit distinct transcriptional signatures detectable using single-cell RNA sequencing. Our first aim is to establish a computational pipeline capable of calling mtDNA mutations at single-cell resolution and apply this computational tool to scRNA-seq data from primary RCC tumors. Our second aim will determine whether transcriptional changes are associated with the presence of a mtDNA mutation in a tumor cell using differential expression approaches suited to scRNA-seq data. The primary innovation of this work will be its characterization of a highly prevalent but largely ignored category of mutations in RCC via a repurposing of a groundbreaking, high-resolution sequencing technology. Results from this work have the potential to shed light both on the structure of intratumoral heterogeneity in RCC tumors and to inform future analysis of potential therapeutic vulnerabilities in mtDNA-mutant RCC cells.